package com.cjh.wc;


import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.AggregateOperator;
import org.apache.flink.api.java.operators.DataSource;
import org.apache.flink.api.java.operators.FlatMapOperator;
import org.apache.flink.api.java.operators.UnsortedGrouping;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.util.Collector;


/**
 * @author chenjiahao
 * 批处理：获取全部数据之后进行处理
 */
public class BatchWordCount {

    public static void main(String[] args) throws Exception {
        // 1.创建执行环境
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

        // 2.从文件中读取数据
        DataSource<String> lineDataSource = env.readTextFile("input/words.txt");

        // 3. 将每行数据进行分词，转换成二元组类型（类似map）
        FlatMapOperator<String, Tuple2<String, Long>> wordAndOneTuple = lineDataSource.flatMap((String line, Collector<Tuple2<String, Long>> out) -> {
            // 将一行文本进行分词
            String[] words = line.split(" ");
            // 将每个单词转换为二元组输出
            for (String word : words) {
                out.collect(Tuple2.of(word, 1L));
            }
        }).returns(Types.TUPLE(Types.STRING, Types.LONG));


        // 4.按照word进行分组
        UnsortedGrouping<Tuple2<String, Long>> wordAndOneGroup = wordAndOneTuple.groupBy(0);

        // 5.分组内进行聚合统计
        AggregateOperator<Tuple2<String, Long>> sum = wordAndOneGroup.sum(1);

        // 6.打印结果
        sum.print();

        /**
         * 执行结果
         * (no,1)
         * (flink,1)
         * (world,1)
         * (hello,3)
         * (java,2)
         * 批处理不需要挂着服务获取到一整批数据之后再进行数据处理
         */



    }
}
